Uni-LoRA: Ultra-Efficient Parameter Reduction For LLM Training Low-Rank Adaptation (LoRA) revolutionized how we fine-tune large language models by introducing parameter-efficient training methods that constrain weight updates to low-rank matrix decompositions (Hu... computational efficiency isometric projections linear algebra LoRA machine learning mathematics neural networks optimization parameter efficiency projection methods
Scaling Laws Unveiled: The Mathematical Blueprint Behind Smarter, Cheaper AI Models Training a state-of-the-art language model can cost tens of millions of dollars and months of computation time, not to mention the expertise needed for development. Yet until now, researchers have bee... AI Chinchilla deep learning GPT-3 language models machine learning neural networks optimization principal component analysis scaling laws statistical methodology
Neural Networks Are Transforming 3D Rendering: Inside Microsoft's RenderFormer 3D rendering powers our most captivating digital experiences, from blockbuster movies to cutting-edge virtual reality. Traditionally, this field has relied on physics-based methods to recreate the int... 3D rendering AI research computer graphics deep learning machine learning neural networks RenderFormer SIGGRAPH
How Global Teams Charted the First Brain-Wide Map of Decision-Making in Mice If we could observe an entire brain as it navigates rapid-fire choices, what would insights would it reveal? Thanks to an unprecedented international collaboration we are getting closer to an answer. ... brain mapping collaborative research data sharing decision-making mouse studies neural networks neuroscience
Agentic Neural Networks: Self-Evolving Multi-Agent Systems Through Textual Backpropagation The landscape of artificial intelligence is rapidly evolving as researchers explore new ways to harness the collaborative power of multiple Large Language Models (LLMs). A groundbreaking paper from Lu... artificial intelligence LLMs multi-agent systems neural networks optimization textual backpropagation
How Tokenizers Are Transforming AI Image Editing and Generation Recent innovations from MIT researchers are leveraging the hidden potential of neural networks called tokenizers for fast, flexible, and resource-efficient image manipulation. Tokenizers: More Than Co... AI computer vision image editing image generation machine learning MIT research neural networks tokenizers
Dynamic Node Pruning: Improving LLM Efficiency Inspired by the Human Brain As artificial intelligence continues to scale, large language models (LLMs) face mounting challenges in computational cost and energy usage. But what if these models could intelligently activate only ... AI efficiency deep learning dynamic pruning LLM model optimization neural networks sustainability
Vision-Based Learning Is Giving Robots a Sense of Self What if a we could program a machine that figures out how its body works the same way a child learns to wiggle their fingers, by observing and experimenting. This is the concept behind the Neural Jaco... autonomous systems computer vision machine learning neural networks robotics self-awareness soft robotics
Machine Learning Reveals the Hidden Complexity of Games Have you ever wondered why some things feel easy to master while others seem endlessly perplexing? Recent research in machine learning is shedding light on this puzzle, uncovering the hidden layers th... behavioral economics complexity decision-making game theory human behavior machine learning neural networks
Demystifying AI: Open-Source Circuit Tracing Tools Illuminate Neural Networks Artificial intelligence has made remarkable strides, but understanding how models arrive at their answers remains a daunting challenge. Anthropic’s new open-source circuit tracing tools promise to bri... AI research AI transparency attribution graphs circuit tracing interpretability language models neural networks open source